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Anthropic practice

Performance Engineer, Inference Systems mock interview

Practice for a Performance Engineer, Inference Systems round at Anthropic. The AI interviewer asks out loud, follows up, and scores your answers after the session.

ML / AICUDAC++Triton
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What this interview will probe

This role optimizes the systems that serve Claude to millions of users, squeezing maximum throughput and minimum latency from large GPU clusters running frontier transformers. Work spans kernel-level optimization, batching and scheduling, and end-to-end profiling of the inference path. A technical interview would probe GPU performance fundamentals, the mechanics of LLM serving (KV cache management, speculative decoding, continuous batching), and how to find and fix the bottleneck limiting tokens-per-second in a production serving stack.

ExoForm is not affiliated with Anthropic. This is an independent practice page.

Stack

CUDAC++Triton

Related practice pages

FAQ

How should I prepare for a Performance Engineer, Inference Systems interview?

Read the role brief, refresh the core stack, and practice explaining tradeoffs out loud. Live interviews test clarity as much as knowledge.

What do I get after the interview?

ExoForm gives you an overall score, a verdict, competency scores, and answer-by-answer feedback.

Can I use my own job description instead?

Yes. You can paste any job description and run a custom interview instead of starting from the catalog.